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Ontology Supported Patent Search Architecture with Natural Language Analysis and Fuzzy Rules

  • Daniela BoshnakoskaEmail author
  • Ivan Chorbev
  • Danco Davcev
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 207)

Abstract

We have recently witnessed a rapid growth in scientific information retrieval research related to patents. Retrieving relevant information from and about patents is a non-trivial task and poses many technical challenges. In this paper we present a new approach to patent search that combines semantic knowledge and ontologies used to annotate patents processed with natural language processing tools. The architecture uses fuzzy logic rules to organize the annotated patents and achieve more precise retrieval. Our approach to combine proven techniques in a composite architecture showed improved results compared to pure textual based indexing and retrieval. We also showed that results ranked using semantic annotation are better than results based on simple keyword frequencies.

Keywords

Ontology semantic web patent search patent mining semantic annotations Natural Language Processing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Daniela Boshnakoska
    • 1
    Email author
  • Ivan Chorbev
    • 2
  • Danco Davcev
    • 1
  1. 1.University for Information Science and Technology “St. Paul the Apostle”OhridR. Macedonia
  2. 2.Faculty of Computer Science and EngineeringSs. Cyril and Methodius UniversitySkopjeMacedonia

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